Description Usage Arguments Details Value Author(s) References See Also Examples

Using auxiliary information from the RMA robust fit, differential splicing can be used

1 |

`object` |
a ProbeLevelModel object (from package aroma.affymetrix). In future, support will be added for |

`nSamples` |
number of random samples to take for simulated null distribution. |

`seed` |
seed for random number generator. |

`cls` |
variable giving the class (aligned with the columns or sample names of the input object). |

`verbose` |
logical, whether to display progress. |

`idsToUse` |
indices of the units to calculate FIRMAGene scores for. |

`minProbes` |
minimum number of probes to operate on. |

Basically, the following steps take place:

* gather the residual from the object in question * standardize the residuals * calculate the MUF (maximum partial sum) score for the observed data * calculate the MUF (maximum partial sum) score for the simulated null data * compare the observed scores to the null distibution

'FGset' object

Mark Robinson

Robinson MD and Speed TP (2009). ...

topSplices

1 2 3 4 | ```
## not run
# hgnetaffx <- read.csv("HuGene-1_0-st-v1.na25.hg18.transcript.csv",sep=",",skip=19,header=TRUE,comment.char="")
# u <- which(getUnitNames(cdf) %in% hgnetaffx$probeset_id[hgnetaffx$category == "main" & hgnetaffx$total_probes > 7 & hgnetaffx$total_probes < 200])
# fg <- FIRMAGene(plm, idsToUse=u, cls=cls)
``` |

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